Factors governing speech reception benefits of adaptive linear filtering for listeners with sensorineural hearing loss.
Adaptive linear filtering can improve effective speech-to-noise ratios by attenuating spectral regions with intense noise components to reduce the noise's spread of masking onto speech in neighboring regions. This mechanism was examined in static listening conditions for seven individuals with sensorineural hearing loss. Subjects were presented with nonsense syllables in an intense octave-band noise centered on 0.5, 1, or 2 kHz. The nonsense syllables were amplified to maximize. the articulation index; the noises were the same for all subjects. The processing consisted of applying frequency-selective attenuation to the speech-plus-noise with the goal of attenuating the frequency region containing the noise by various amounts. Consonant recognition scores and noise masking patterns were collected in all listening conditions. When compared with masking patterns obtained from normal-hearing subjects, all hearing-impaired subjects had higher masked thresholds at frequencies below, within, and above the masker band except for one subject who demonstrated additional masking above the masker only. Frequency-selective attenuation resulted in both increases and decreases in consonant recognition scores. Increases were associated with a release from upward spread of masking. Decreases were associated with applying too much attenuation such that speech energy within the masker band that was audible before processing was partially below threshold after processing. Fletcher's [Speech and Hearing in Communication (Van Nostrand, New York, 1953)] version of articulation theory (without modification) accounted for individual subject differences within the range of variability associated with the consonant recognition test in almost every instance. Hence, primary factors influencing speech reception benefits are characterized by articulation theory. Fletcher's theory appears well-suited to guide the design of control algorithms that will maximize speech recognition for individual listeners.
Rankovic
C M
CM
Northeastern University, Department of Speech-Language Pathology and Audiology, Boston, Massachusetts 02115, USA.
D000328:Adult; D000368:Aged; D001309:Auditory Threshold; D006310:Hearing Aids; D006316:Hearing Loss, High-Frequency / Q000534:rehabilitation; D006319:Hearing Loss, Sensorineural / Q000534:rehabilitation*; D006801:Humans; D008875:Middle Aged; D010470:Perceptual Masking; D010700:Phonetics; D013067:Speech Perception